Dytective: towards detecting dyslexia across languages using an online game

Luz Rello, Kristin Williams, Abdullah Ali, N. C. White, Jeffrey P. Bigham
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引用次数: 22

Abstract

At least 10% of the global population has dyslexia. In the United States and Spain, dyslexia is associated with a large percentage of school drop out. Current methods to detect risk of dyslexia are language specific, expensive, or do not scale well because they require a professional or extensive equipment. A central challenge to detecting dyslexia is handling its differing manifestations across languages. To address this, we designed a browser-based game, Dytective, to detect risk of dyslexia across the English and Spanish languages. Dytective consists of linguistic tasks informed by analysis of common errors made by persons with dyslexia. To evaluate Dytective, we conducted a user study with 60 English and Spanish speaking children between 7 and 12 years old. We found children with and without dyslexia differed significantly in their performance on the game. Our results suggest that Dytective is able to differentiate school age children with and without dyslexia in both English and Spanish speakers.
Dytective:使用在线游戏检测跨语言阅读障碍
全球至少有10%的人患有阅读障碍。在美国和西班牙,阅读障碍与很大比例的辍学率有关。目前检测阅读障碍风险的方法是针对特定语言的,昂贵的,或者因为需要专业或广泛的设备而不能很好地扩展。检测阅读障碍的一个核心挑战是如何处理不同语言之间的不同表现。为了解决这个问题,我们设计了一个基于浏览器的游戏,Dytective,来检测英语和西班牙语的阅读障碍风险。词汇是通过分析阅读障碍患者的常见错误而完成的语言任务。为了评估侦探,我们对60名7至12岁的英语和西班牙语儿童进行了一项用户研究。我们发现有阅读障碍和没有阅读障碍的孩子在游戏中的表现有很大的不同。我们的研究结果表明,Dytective能够区分英语和西班牙语的学龄儿童有和没有阅读障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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